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Estimation of solution norms and stability for time-dependent nonlinear systems is ubiquitous in numerous applied and control problems. Yet, practically valuable results are rare in this area. This paper develops a novel approach, which…

Dynamical Systems · Mathematics 2018-08-29 Mark A. Pinsky , Steve Koblik

I review the basic concepts for the spectrophotometric and chemical evolution of galaxies, contrast various approaches and discuss their respective advantages and shortcomings, both for the interpretation of nearby and high redshift…

Astrophysics · Physics 2007-05-23 U. Fritze-v. Alvensleben

Context. Mixing by convective overshooting has long been suggested to play an important role for the amount of hydrogen available to nuclear burning in convective cores of stars. The best way to model this effect is still debated. Aims. We…

Solar and Stellar Astrophysics · Physics 2022-11-16 F. Kupka , F. Ahlborn , A. Weiss

We describe our 3-dimensional numerical relativity code for the evolution of inhomogeneous cosmologies. During the evolution the constraint equations are monitored but not solved. The code has been tested against perturbation theory with…

Astrophysics · Physics 2009-10-22 Hannu Kurki-Suonio , Pablo Laguna , Richard A. Matzner

1D stellar evolution calculations produce uncertain predictions for quantities like the age, core mass, core compactness, and nucleo-synthetic yields; a key source of uncertainty is the modeling of interfaces between regions that are…

We study the convergence of stochastic time-discretization schemes for evolution equations driven by random velocity fields, including examples like stochastic gradient descent and interacting particle systems. Using a unified framework…

Functional Analysis · Mathematics 2025-05-28 Giulia Cavagnari , Giuseppe Savaré , Giacomo Enrico Sodini

In engineering, it is a common desire to couple existing simulation tools together into one big system by passing information from subsystems as parameters into the subsystems under influence. As executed at fixed time points, this data…

Numerical Analysis · Computer Science 2017-06-23 Thilo Moshagen

A new numerical method is introduced to study the problem of time evolution of generic non-linear dynamical systems in four-dimensional spacetimes. It is assumed that the time level surfaces are foliated by a one-parameter family of…

General Relativity and Quantum Cosmology · Physics 2015-06-05 Peter Csizmadia , Andras Laszlo , Istvan Racz

We study the problem of entropy calibration, which asks whether a language model's entropy over generations matches its log loss on human text. Past work found that models are miscalibrated, with entropy per step increasing as generations…

Computation and Language · Computer Science 2026-01-14 Steven Cao , Gregory Valiant , Percy Liang

Spectra of late-type stars are usually analyzed with static model atmospheres in local thermodynamic equilibrium (LTE) and a homogeneous plane-parallel or spherically symmetric geometry. The energy balance requires particular attention, as…

Astrophysics · Physics 2009-11-06 Carlos Allende Prieto , Paul S. Barklem , Martin Asplund , Basilio Ruiz Cobo

We present a new stellar atmosphere interpolator which we will use to compute stellar population models based on empirical and/or synthetic spectra. We combined observed and synthetic stellar spectra in order to achieve more or less uniform…

Instrumentation and Methods for Astrophysics · Physics 2015-11-24 Nikolay Podorvanyuk , Igor Chilingarian , Ivan Katkov

This paper introduces the idea that the general mixing inequality obeyed by evolving stellar phase densities may place useful constraints on the possible history of the over-all galaxy population. We construct simple models for the full…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-19 Michael R. Merrifield

Statistical inference in observational science typically relies on a fundamental assumption: as sample size increases and uncertainties decrease, the inferred results should converge to the true physical quantities. This assumption…

Machine Learning · Computer Science 2026-05-01 Zhipeng Zhang

We assess the systematic uncertainties in stellar evolutionary calculations for low- to intermediate-mass, main-sequence stars. We compare published stellar tracks from several different evolution codes with our own tracks computed using…

Solar and Stellar Astrophysics · Physics 2016-02-17 R. J. Stancliffe , L. Fossati , J. -C. Passy , F. R. N. Schneider

We present a new set of stellar interior and synthesis models for predicting the integrated emission from stellar populations in star clusters and galaxies of arbitrary age and metallicity. This work differs from existing spectral synthesis…

Astrophysics · Physics 2009-11-10 Raul Jimenez , James MacDonald , James Dunlop , Paolo Padoan , John Peacock

Deuterium is created during Big Bang Nucleosynthesis, and, in contrast to the other light stable nuclei, can only be destroyed thereafter by fusion in stellar interiors. In this paper we study the cosmic evolution of the deuterium abundance…

Astrophysics of Galaxies · Physics 2016-03-09 Irina Dvorkin , Elisabeth Vangioni , Joseph Silk , Patrick Petitjean , Keith A. Olive

Modern generative models exhibit unprecedented capabilities to generate extremely realistic data. However, given the inherent compositionality of the real world, reliable use of these models in practical applications requires that they…

Machine Learning · Computer Science 2025-07-29 Maya Okawa , Ekdeep Singh Lubana , Robert P. Dick , Hidenori Tanaka

The stellar velocity dispersion ($\sigma$) of massive elliptical galaxies is a key ingredient in breaking the mass-sheet degeneracy and obtaining precise and accurate cosmography from gravitational time delays. The relative uncertainty on…

Over the last decades, evolutionary population synthesis models have powered an unmatched leap forward in our understanding of galaxies. From dating the age of the first galaxies in the Universe to detailed measurements of the chemical…

Astrophysics of Galaxies · Physics 2024-11-13 I. Martín-Navarro , A. Vazdekis

Diffusion models have demonstrated exceptional performances in various fields of generative modeling, but suffer from slow sampling speed due to their iterative nature. While this issue is being addressed in continuous domains, discrete…

Machine Learning · Computer Science 2025-05-12 Satoshi Hayakawa , Yuhta Takida , Masaaki Imaizumi , Hiromi Wakaki , Yuki Mitsufuji